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Neural Context Reinstatement Predicts Memory Misattribution

Author(s)
Gershman, Samuel J.; Schapiro, Anna C.; Hupbach, Almut; Norman, Kenneth A.
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Abstract
What causes new information to be mistakenly attributed to an old experience? Some theories predict that reinstating the context of a prior experience allows new information to be bound to that context, leading to source memory confusion. To examine this prediction, we had human participants study two lists of items (visual objects) on separate days while undergoing functional magnetic resonance imaging. List 1 items were accompanied by a stream of scene images during the intertrial interval, but list 2 items were not. As in prior work by Hupbach et al. (2009), we observed an asymmetric pattern of misattributions on a subsequent source memory test: participants showed a strong tendency to misattribute list 2 items to list 1 but not vice versa. We hypothesized that these memory errors were due to participants reinstating the list 1 context during list 2. To test this hypothesis, we used a pattern classifier to measure scene-related neural activity during list 2 study. Because scenes were visually present during list 1 but not list 2, scene-related activity during list 2 study can be used as a time-varying neural indicator of how much participants were reinstating the list 1 context during list 2 study. In keeping with our hypothesis, we found that prestimulus scene activation during the study of list 2 items was significantly higher for items subsequently misattributed to list 1 than for items subsequently correctly attributed to list 2. We conclude by discussing how these findings relate to theories of memory reconsolidation.
Date issued
2013-05
URI
http://hdl.handle.net/1721.1/83867
Department
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Journal
Journal of Neuroscience
Publisher
Society for Neuroscience
Citation
Gershman, S. J., A. C. Schapiro, A. Hupbach, and K. A. Norman. “Neural Context Reinstatement Predicts Memory Misattribution.” Journal of Neuroscience 33, no. 20 (May 15, 2013): 8590-8595.
Version: Final published version
ISSN
0270-6474
1529-2401

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